A Summary of the ALQAC 2021 Competition

TL;DR

The paper summarizes the ALQAC 2021 competition, which involved tasks on legal text retrieval, entailment prediction, and question answering to develop systems that assess lawfulness of statements.

Contribution

It provides an overview of the competition's tasks, participating teams, approaches, and results, highlighting progress in automated legal question answering.

Findings

Multiple approaches achieved successful results in legal text tasks.

Diverse methods were employed by teams, indicating no single dominant approach.

The competition fostered advancements in legal NLP applications.

Abstract

We summarize the evaluation of the first Automated Legal Question Answering Competition (ALQAC 2021). The competition this year contains three tasks, which aims at processing the statute law document, which are Legal Text Information Retrieval (Task 1), Legal Text Entailment Prediction (Task 2), and Legal Text Question Answering (Task 3). The final goal of these tasks is to build a system that can automatically determine whether a particular statement is lawful. There is no limit to the approaches of the participating teams. This year, there are 5 teams participating in Task 1, 6 teams participating in Task 2, and 5 teams participating in Task 3. There are in total 36 runs submitted to the organizer. In this paper, we summarize each team's approaches, official results, and some discussion about the competition. Only results of the teams who successfully submit their approach description paper are reported in this paper.